Applied Metaphors: Learning TRIZ, Complexity, Data/Stats/ML using Metaphors
  1. Lab-8: Did you ever see such a thing as a drawing of a muchness?
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    On this page

    • Setting up R Packages
    • Introduction
    • htmlwidgets usage
      • Using networkD3
      • Creating a Sankey Diagram.
    • Using threejs ( WIP )
      • graphjs usage
    • globejs usage
    • Using scatterplot3js and friends
    • References

    Lab-8: Did you ever see such a thing as a drawing of a muchness?

    Working with htmlwidgets in R!

    Author

    Arvind Venkatadri

    Published

    July 10, 2022

    Modified

    July 17, 2025

    Setting up R Packages

    # Data manipulation and data sources
    options(htmltools.preserve.raw = FALSE, echo = TRUE)
    library(tidygraph)
    library(igraph)
    library(palmerpenguins)
    library(igraphdata)
    
    
    # To render htmlwidgets as iframe widgets
    # https://communicate-data-with-r.netlify.app/docs/communicate/htmlwidgets-in-documents/
    # library(widgetframe)
    
    # htmlwidget related libraries
    library(htmlwidgets)
    
    
    # Widget Libraries
    library(leaflet)
    library(plotly)
    library(DT)
    library(echarts4r)
    library(echarts4r.assets)
    library(canvasXpress)
    library(rgl)
    library(networkD3)
    library(threejs)
    library(slickR)
    library(crosstalk)
    # Linkable widgets in crosstalk - github repo only
    # devtools::install_github("kent37/summarywidget")
    library(summarywidget)
    library(tidyverse)

    Introduction

    There are very many great JavaScript libraries for creating eye-popping and even interactive charts! And these are now available in R, and can be invoked using R code! So we can β€œuse JavaScript” in R, as it were, without knowing JavaScript! And create something like this:



    Unlike the Dormouse, no complaints!

    We will explore a few them, as an alternative to ggplot !!

    This may be too much of a good thing, or a much of muchness but then, we can always use more then one way of telling our stories!!

    htmlwidgets usage

    htmlwidgets creates, well, widgets, that can visualize data in many ways. HTML widgets work just like R plots except they produce interactive web visualizations. These can be used in RMarkdown, in flexdashboards, and in shiny apps.

    All the possible widgets ( 127 of them on CRAN ) are listed here: https://gallery.htmlwidgets.org/

    Some packages that offer widgets for use in htmlwidgets:

    1. networkD3:
    • Force directed networks with simpleNetwork and forceNetwork
    • Sankey diagrams with sankeyNetwork
    • Radial networks with radialNetwork
    • Dendro networks with dendroNetwork

    Using networkD3

    library(networkD3)
    data("karate")
    
    # Make separate data frames for edges and nodes
    # networkD3 needs indices starting from 1
    karate_edges <- karate %>%
      as_tbl_graph() %>%
      tidygraph::activate(edges) %>%
      as.data.frame() %>%
      dplyr::mutate(source = from - 1, target = to - 1) %>%
      rename(value = weight) %>%
      select(source, target, value)
    karate_edges
    karate_nodes <- karate %>%
      as_tbl_graph() %>%
      tidygraph::activate(nodes) %>%
      as.data.frame() %>%
      dplyr::mutate(group = as.character(Faction)) %>%
      select(name, label, group, color)
    karate_nodes
    simpleNetwork(karate_edges,
      charge = -50,
      fontSize = 12, zoom = FALSE,
      fontFamily = "serif"
    )

    forceNetwork(
      Links = karate_edges,
      Nodes = karate_nodes,
      Value = "value",
      # width of edges, dbl
      NodeID = "name",
      # chr
      Group = "group",
      # Node group, chr
      # Nodesize = "label" # chr !!!
      # linkColour = "value"
    )

    Creating a Sankey Diagram.

    # Code is not working need to fix
    # No nodes showing up...
    UCB_graph <-
      UCBAdmissions %>%
      as.data.frame() %>%
      # select(Gender, Admit, Dept, Freq) %>%
      as_tbl_graph()
    UCB_graph
    
    UCB_nodes <- UCB_graph %>%
      activate(nodes) %>%
      as_tibble()
    UCB_nodes
    
    UCB_links <- UCB_graph %>%
      activate(edges) %>%
      as_tibble() %>%
      dplyr::mutate(from = from - 1, to = to - 1)
    UCB_links
    
    sankeyNetwork(
      Links = UCB_links,
      Nodes = UCB_nodes,
      Source = "from",
      Target = "to",
      Value = "Freq",
      LinkGroup = "Dept",
      fontSize = 20,
      fontFamily = "Arial"
    )

    simpleNetwork, forceNetwork and sankeyNetwork use a similar node and link data structure, organized as two data frames (not tibbles)

    chordNetwork uses an association matrix type of matrix or a data frame organized in the same way, where entry (n,m) represents the strength of the link from group n to group m. Matrix needs to be square !! β€œColumn names” and β€œRow names” need to be the same if the data is a data.frame.

    data <- matrix(rpois(n = 16, lambda = 50),
      nrow = 4, ncol = 4
    )
    chordNetwork(data,
      labels = c("A", "B", "C", "D")
    )

    Using threejs ( WIP )

    1. https://bwlewis.github.io/rthreejs/
    2. https://bwlewis.github.io/rthreejs/crosstalk.html

    graphjs usage

    data("LeMis") # igraph object
    LeMis
    IGRAPH b7852d9 U--- 77 254 -- 
    + attr: label (v/c), color (v/c), size (v/n)
    + edges from b7852d9:
     [1]  1-- 2  1-- 3  1-- 4  3-- 4  1-- 5  1-- 6  1-- 7  1-- 8  1-- 9  1--10
    [11] 11--12  4--12  3--12  1--12 12--13 12--14 12--15 12--16 17--18 17--19
    [21] 18--19 17--20 18--20 19--20 17--21 18--21 19--21 20--21 17--22 18--22
    [31] 19--22 20--22 21--22 17--23 18--23 19--23 20--23 21--23 22--23 17--24
    [41] 18--24 19--24 20--24 21--24 22--24 23--24 13--24 12--24 24--25 12--25
    [51] 25--26 24--26 12--26 25--27 12--27 17--27 26--27 12--28 24--28 26--28
    [61] 25--28 27--28 12--29 28--29 24--30 28--30 12--30 24--31 31--32 12--32
    [71] 24--32 28--32 12--33 12--34 28--34 12--35 30--35 12--36 35--36 30--36
    + ... omitted several edges
    # V(LeMis)$label
    # V(LeMis)$color
    graphjs(LeMis,
      layout = list( # animates between a list of layouts
        # layouts need to be 3D layouts
        # Or each can be a 3 column matrix with n(rows) = n(vertices)
        layout_randomly(LeMis, dim = 3),
        layout_on_sphere(LeMis),
        layout_with_drl(LeMis, dim = 3), # note! somewhat slow...
        layout_with_fr(LeMis, dim = 3, niter = 30)
      ),
      main = list("random layout", "sphere layout", "drl layout", "fr layout"),
      fpl = 300
    )

    globejs usage

    Plot points, arcs and images on a globe in 3D using three.js. The globe can be rotated and and zoomed. Great Circles and historical routes are a good idea for this perhaps.

    Refer to this page for more ideas http://bwlewis.github.io/rthreejs/globejs.html

    # Random Lats and Longs
    lat <- rpois(10, 60) + rnorm(10, 80)
    long <- rpois(10, 60) + rnorm(10, 10)
    
    # Random "Spike" heights for each location. Population? Tourists? GDP?
    value <- rpois(10, lambda = 80)
    
    globejs(lat = lat, long = long)

    globejs(
      lat = lat,
      long = long,
    
      # random heights of the Spikes (!!) at lat-long combo
      value = value,
      color = "red",
      # Zoom factor, default is 35
      fov = 50
    )

    globejs(
      lat = lat,
      long = long,
      value = value,
      color = "red",
      pointsize = 4, # width of the columns
      # Zoom position
      fov = 35,
      # initial position of the globe
      rotationlat = 0.6, #  in RADIANS !!! Good Heavens!!
      rotationlong = 0.2 #  in RADIANS !!! Good Heavens!!
    )

    globejs(
      lat = lat,
      long = long,
      value = value,
      color = "red",
      pointsize = 4,
      fov = 35,
      rotationlat = 0.6,
      rotationlong = 0.2,
      lightcolor = "#aaeeff",
      emissive = "#0000ee",
      bodycolor = "#ffffff",
      bg = "grey"
    )

    # Plotting arcs on the globe
    # Requires 4 column data frame for start and end lat and long
    
    arcs <- data.frame(
      start_lat = runif(10, min = -20, max = 20),
      start_lon = runif(10, min = -20, max = 20),
      end_lat = runif(10, min = -20, max = 20),
      end_lon = runif(10, min = -20, max = 20) + 60
    )
    arcs
    globejs(
      arcs = arcs,
      arcsColor = "gold",
      arcsLwd = 4,
      arcsHeight = 0.6,
      arcsOpacity = 1,
      rotationlat = 0,
      rotationlong = -2.2,
      bg = "lightblue", atmosphere = FALSE,
      pointsize = 2
    )

    threejs contains a dataset called flights obtained from Callum Prentice’s FlightStream page: http://callumprentice.github.io/apps/flight_stream/index.html

    threejs::flights() %>% head()
    frequent_destinations <-
      threejs::flights() %>%
      dplyr::group_by(dest_lat, dest_long) %>%
      count(sort = TRUE) %>%
      ungroup() %>%
      slice_max(n = 10, order_by = n)
    frequent_destinations
    frequent_flights <- threejs::flights() %>%
      semi_join(frequent_destinations,
        by = c("dest_lat" = "dest_lat", "dest_long" = "dest_long")
      ) %>%
      unique()
    
    frequent_flights %>%
      kableExtra::kbl() %>%
      kableExtra::kable_paper(full_width = TRUE) %>%
      kableExtra::kable_styling(bootstrap_options = c("striped", "condensed", "responsive")) %>%
      kableExtra::scroll_box(width = "700px", height = "500px")
    origin_lat origin_long dest_lat dest_long
    1 40.657633 17.947033 47.464722 8.549167
    2 44.828335 -0.715556 47.464722 8.549167
    3 51.382669 -2.719089 47.464722 8.549167
    4 34.875117 33.624850 47.464722 8.549167
    5 27.931886 -15.386586 47.464722 8.549167
    6 25.557111 34.583711 47.464722 8.549167
    7 40.783200 -91.125500 41.978603 -87.904842
    8 39.834564 -88.865689 41.978603 -87.904842
    9 13.681108 100.747283 1.350189 103.994433
    10 -12.408333 130.872660 1.350189 103.994433
    11 19.934856 110.458961 1.350189 103.994433
    12 30.229503 120.434453 1.350189 103.994433
    13 22.308919 113.914603 1.350189 103.994433
    14 8.113200 98.316872 1.350189 103.994433
    15 34.434722 135.244167 25.077731 121.232822
    16 2.745578 101.709917 1.350189 103.994433
    17 14.508647 121.019581 1.350189 103.994433
    18 5.297139 100.276864 1.350189 103.994433
    19 -31.940278 115.966944 1.350189 103.994433
    20 11.546556 104.844139 1.350189 103.994433
    21 13.410666 103.812840 1.350189 103.994433
    22 16.907305 96.133222 1.350189 103.994433
    23 10.818797 106.651856 1.350189 103.994433
    24 1.350189 103.994433 25.077731 121.232822
    25 51.132767 13.767161 47.464722 8.549167
    26 42.760277 10.239445 47.464722 8.549167
    27 46.991067 15.439628 47.464722 8.549167
    28 47.793304 13.004333 47.464722 8.549167
    29 21.539400 109.294000 34.447119 108.751592
    30 29.719217 106.641678 40.080111 116.584556
    31 29.719217 106.641678 31.143378 121.805214
    32 29.719217 106.641678 34.447119 108.751592
    33 30.578528 103.947086 40.080111 116.584556
    34 30.578528 103.947086 31.143378 121.805214
    35 30.578528 103.947086 34.447119 108.751592
    36 25.935064 119.663272 34.447119 108.751592
    37 34.490900 102.371900 34.447119 108.751592
    38 45.623403 126.250328 34.447119 108.751592
    39 24.992364 102.743536 25.077731 121.232822
    40 24.992364 102.743536 34.447119 108.751592
    41 29.297778 90.911944 34.447119 108.751592
    42 35.046100 118.412000 34.447119 108.751592
    43 36.857214 117.215992 34.447119 108.751592
    44 43.907106 87.474244 34.447119 108.751592
    45 38.269200 109.731000 34.447119 108.751592
    46 36.898731 30.800461 47.464722 8.549167
    47 27.178317 33.799436 47.464722 8.549167
    48 42.572778 21.035833 47.464722 8.549167
    50 41.961622 21.621381 47.464722 8.549167
    51 50.865917 7.142744 51.477500 -0.461389
    52 50.865917 7.142744 48.110278 16.569722
    53 50.865917 7.142744 47.464722 8.549167
    54 52.461056 9.685078 48.110278 16.569722
    55 53.630389 9.988228 51.477500 -0.461389
    56 53.630389 9.988228 48.110278 16.569722
    57 53.630389 9.988228 47.464722 8.549167
    58 48.689878 9.221964 48.110278 16.569722
    59 52.559686 13.287711 48.110278 16.569722
    60 10.307542 123.979439 1.350189 103.994433
    61 15.185833 120.560278 1.350189 103.994433
    62 10.713044 122.545297 1.350189 103.994433
    63 14.508647 121.019581 40.080111 116.584556
    64 14.508647 121.019581 31.143378 121.805214
    66 14.508647 121.019581 25.077731 121.232822
    67 12.994414 80.180517 1.350189 103.994433
    68 40.560000 109.997000 34.447119 108.751592
    69 31.780019 117.298436 31.143378 121.805214
    70 24.992364 102.743536 40.080111 116.584556
    71 24.992364 102.743536 31.143378 121.805214
    73 26.538522 106.800703 1.350189 103.994433
    74 26.883333 100.233330 34.447119 108.751592
    75 24.401100 98.531700 40.080111 116.584556
    77 5.937208 116.051181 31.143378 121.805214
    78 13.681108 100.747283 31.143378 121.805214
    79 43.541200 125.120100 31.143378 121.805214
    80 33.511306 126.493028 31.143378 121.805214
    82 18.766847 98.962644 31.143378 121.805214
    83 38.965667 121.538600 31.143378 121.805214
    84 29.102800 110.443000 31.143378 121.805214
    85 22.308919 113.914603 31.143378 121.805214
    86 8.113200 98.316872 31.143378 121.805214
    87 45.623403 126.250328 31.143378 121.805214
    88 33.149700 130.302000 31.143378 121.805214
    89 36.181083 140.415444 31.143378 121.805214
    90 22.577094 120.350006 31.143378 121.805214
    91 34.434722 135.244167 31.143378 121.805214
    93 25.218106 110.039197 31.143378 121.805214
    94 36.117000 103.617000 31.143378 121.805214
    95 22.149556 113.591558 31.143378 121.805214
    96 31.143378 121.805214 1.350189 103.994433
    97 31.143378 121.805214 25.077731 121.232822
    98 31.197875 121.336319 34.447119 108.751592
    99 41.382400 123.290100 34.447119 108.751592
    100 38.280686 114.697300 25.077731 121.232822
    102 22.006400 113.376000 31.143378 121.805214
    103 19.088686 72.867919 51.477500 -0.461389
    104 19.088686 72.867919 1.350189 103.994433
    105 50.901389 4.484444 43.677223 -79.630556
    106 28.566500 77.103088 51.477500 -0.461389
    107 28.566500 77.103088 1.350189 103.994433
    109 37.936358 23.944467 51.477500 -0.461389
    110 37.936358 23.944467 48.110278 16.569722
    111 35.339719 25.180297 48.110278 16.569722
    112 41.669167 44.954722 48.110278 16.569722
    113 35.040222 -106.609194 41.978603 -87.904842
    114 57.201944 -2.197778 51.477500 -0.461389
    115 5.605186 -0.166786 51.477500 -0.461389
    116 36.674900 -4.499106 51.477500 -0.461389
    117 42.557100 -92.400300 41.978603 -87.904842
    118 31.722556 35.993214 41.978603 -87.904842
    119 52.308613 4.763889 51.477500 -0.461389
    120 59.651944 17.918611 51.477500 -0.461389
    121 43.991922 -76.021739 41.978603 -87.904842
    123 33.636719 -84.428067 51.477500 -0.461389
    124 33.636719 -84.428067 41.978603 -87.904842
    125 24.432972 54.651138 51.477500 -0.461389
    126 24.432972 54.651138 41.978603 -87.904842
    127 30.194528 -97.669889 51.477500 -0.461389
    128 30.194528 -97.669889 41.978603 -87.904842
    129 42.234875 -85.552058 41.978603 -87.904842
    130 26.270834 50.633610 51.477500 -0.461389
    131 41.297078 2.078464 51.477500 -0.461389
    132 41.938889 -72.683222 41.978603 -87.904842
    133 60.293386 5.218142 51.477500 -0.461389
    134 54.618056 -5.872500 51.477500 -0.461389
    135 44.535444 11.288667 51.477500 -0.461389
    136 12.949986 77.668206 51.477500 -0.461389
    137 40.477111 -88.915917 41.978603 -87.904842
    138 36.124472 -86.678194 41.978603 -87.904842
    140 42.364347 -71.005181 51.477500 -0.461389
    141 42.364347 -71.005181 41.978603 -87.904842
    142 50.901389 4.484444 51.477500 -0.461389
    143 47.590000 7.529167 51.477500 -0.461389
    144 47.436933 19.255592 51.477500 -0.461389
    145 42.940525 -78.732167 41.978603 -87.904842
    146 39.175361 -76.668333 51.477500 -0.461389
    147 39.175361 -76.668333 41.978603 -87.904842
    148 49.012779 2.550000 51.477500 -0.461389
    149 49.012779 2.550000 41.978603 -87.904842
    150 35.035278 -85.203808 41.978603 -87.904842
    151 38.138639 -78.452861 41.978603 -87.904842
    152 41.884694 -91.710806 41.978603 -87.904842
    153 41.411689 -81.849794 41.978603 -87.904842
    154 35.214000 -80.943139 51.477500 -0.461389
    155 35.214000 -80.943139 41.978603 -87.904842
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    739 30.121944 31.405556 40.080111 116.584556
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    764 40.060300 113.482000 40.080111 116.584556
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    776 40.692500 -74.168667 31.143378 121.805214
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    779 25.935064 119.663272 40.080111 116.584556
    780 50.026421 8.543125 40.080111 116.584556
    781 50.026421 8.543125 31.143378 121.805214
    782 32.900000 115.816667 40.080111 116.584556
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    784 37.558311 126.790586 40.080111 116.584556
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    787 19.934856 110.458961 40.080111 116.584556
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    798 8.113200 98.316872 40.080111 116.584556
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    801 42.841400 93.669200 40.080111 116.584556
    802 35.552258 139.779694 40.080111 116.584556
    803 21.318681 -157.922428 40.080111 116.584556
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    812 38.481944 106.009167 34.447119 108.751592
    813 40.976922 28.814606 40.080111 116.584556
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    816 29.338600 117.176000 34.447119 108.751592
    817 40.639751 -73.778925 40.080111 116.584556
    818 26.899700 114.737500 40.080111 116.584556
    819 29.733000 115.983000 40.080111 116.584556
    820 24.796400 118.590000 31.143378 121.805214
    821 46.843394 130.465389 40.080111 116.584556
    822 32.857000 103.683000 31.143378 121.805214
    823 28.865000 115.900000 40.080111 116.584556
    824 28.865000 115.900000 31.143378 121.805214
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    829 25.825800 114.912000 40.080111 116.584556
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    831 26.538522 106.800703 31.143378 121.805214
    832 26.538522 106.800703 34.447119 108.751592
    833 25.218106 110.039197 40.080111 116.584556
    835 25.218106 110.039197 34.447119 108.751592
    836 33.942536 -118.408075 40.080111 116.584556
    838 51.148056 -0.190278 40.080111 116.584556
    841 36.117000 103.617000 40.080111 116.584556
    842 36.117000 103.617000 34.447119 108.751592
    843 26.883333 100.233330 40.080111 116.584556
    844 29.297778 90.911944 40.080111 116.584556
    845 24.207500 109.391000 40.080111 116.584556
    846 40.493556 -3.566764 40.080111 116.584556
    847 44.523889 129.568889 40.080111 116.584556
    848 -37.673333 144.843333 31.143378 121.805214
    849 22.149556 113.591558 40.080111 116.584556
    851 31.428100 104.741000 40.080111 116.584556
    853 48.353783 11.786086 40.080111 116.584556
    854 48.353783 11.786086 31.143378 121.805214
    855 34.991389 126.382778 40.080111 116.584556
    856 45.630606 8.728111 40.080111 116.584556
    857 45.630606 8.728111 31.143378 121.805214
    858 47.239628 123.918131 40.080111 116.584556
    859 29.826683 121.461906 40.080111 116.584556
    860 34.858414 136.805408 31.143378 121.805214
    861 31.742042 118.862025 40.080111 116.584556
    862 31.742042 118.862025 34.447119 108.751592
    863 22.608267 108.172442 40.080111 116.584556
    865 35.764722 140.386389 40.080111 116.584556
    866 35.764722 140.386389 31.143378 121.805214
    867 32.070800 120.976000 40.080111 116.584556
    868 26.195814 127.645869 40.080111 116.584556
    871 40.080111 116.584556 31.143378 121.805214
    872 40.080111 116.584556 1.350189 103.994433
    874 40.080111 116.584556 48.110278 16.569722
    875 40.080111 116.584556 34.447119 108.751592
    878 31.143378 121.805214 34.447119 108.751592
    881 22.639258 113.810664 34.447119 108.751592
    882 36.266108 120.374436 34.447119 108.751592
    886 27.912200 120.852000 34.447119 108.751592
    887 31.494400 120.429000 34.447119 108.751592
    898 50.026421 8.543125 25.077731 121.232822
    899 34.796111 138.189444 25.077731 121.232822
    902 19.934856 110.458961 25.077731 121.232822
    904 34.436111 132.919444 25.077731 121.232822
    906 21.318681 -157.922428 25.077731 121.232822
    908 24.344525 124.186983 25.077731 121.232822
    909 22.577094 120.350006 40.080111 116.584556
    911 22.577094 120.350006 1.350189 103.994433
    912 28.865000 115.900000 25.077731 121.232822
    914 31.877222 131.448611 25.077731 121.232822
    915 31.803397 130.719408 25.077731 121.232822
    919 34.858414 136.805408 25.077731 121.232822
    921 26.195814 127.645869 25.077731 121.232822
    923 5.297139 100.276864 25.077731 121.232822
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    928 7.367303 134.544278 25.077731 121.232822
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    935 34.214167 134.015556 25.077731 121.232822
    937 36.648333 137.187500 25.077731 121.232822
    938 25.077731 121.232822 48.110278 16.569722
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    946 21.420428 -77.847433 43.677223 -79.630556
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    997 42.212444 -83.353389 31.143378 121.805214
    999 29.102800 110.443000 25.077731 121.232822
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    1258 42.841400 93.669200 34.447119 108.751592
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    1274 36.898731 30.800461 48.110278 16.569722
    1280 55.408611 37.906111 48.110278 16.569722
    1287 27.178317 33.799436 48.110278 16.569722
    1302 25.557111 34.583711 48.110278 16.569722
    1306 32.011389 34.886667 48.110278 16.569722
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    1392 49.566667 117.329444 40.080111 116.584556
    1395 55.012622 82.650656 40.080111 116.584556
    1408 39.794444 106.799444 34.447119 108.751592
    1410 51.956944 4.437222 48.110278 16.569722
    1424 41.297078 2.078464 47.464722 8.549167
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    1450 43.302061 -8.377256 51.477500 -0.461389
    1467 35.416111 51.152222 51.477500 -0.461389
    1468 35.416111 51.152222 40.080111 116.584556
    1469 35.416111 51.152222 48.110278 16.569722
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    1472 40.467500 50.046667 48.110278 16.569722
    1473 5.765280 103.007000 1.350189 103.994433
    1474 44.941444 17.297501 47.464722 8.549167
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    1478 19.934856 110.458961 34.447119 108.751592
    1484 45.306110 130.996670 40.080111 116.584556
    1490 38.280686 114.697300 34.447119 108.751592
    1495 29.733300 118.256000 34.447119 108.751592
    1500 42.775200 141.692283 31.143378 121.805214
    1501 34.796111 138.189444 31.143378 121.805214
    1504 34.436111 132.919444 31.143378 121.805214
    1508 35.552258 139.779694 1.350189 103.994433
    1509 37.571100 139.064600 31.143378 121.805214
    1513 36.394611 136.406544 31.143378 121.805214
    1514 31.803397 130.719408 31.143378 121.805214
    1515 33.827222 132.699722 31.143378 121.805214
    1518 32.916944 129.913611 31.143378 121.805214
    1525 34.756944 133.855278 31.143378 121.805214
    1527 46.223686 14.457611 48.110278 16.569722
    1528 46.223686 14.457611 47.464722 8.549167
    1536 44.818444 20.309139 48.110278 16.569722
    1537 44.818444 20.309139 47.464722 8.549167
    1539 54.377569 18.466222 47.464722 8.549167
    1540 50.077731 19.784836 47.464722 8.549167
    1541 51.102683 16.885836 47.464722 8.549167
    1542 11.546556 104.844139 31.143378 121.805214
    1550 51.022222 71.466944 48.110278 16.569722
    1551 33.511306 126.493028 40.080111 116.584556
    1559 37.469075 126.450517 48.110278 16.569722
    1560 37.469075 126.450517 34.447119 108.751592
    1561 37.469075 126.450517 43.677223 -79.630556
    1568 52.308613 4.763889 1.350189 103.994433
    1570 52.308613 4.763889 48.110278 16.569722
    1572 52.308613 4.763889 47.464722 8.549167
    1588 35.857497 14.477500 47.464722 8.549167
    1593 19.292778 -81.357750 41.978603 -87.904842
    1597 49.626575 6.211517 48.110278 16.569722
    1612 50.026421 8.543125 41.978603 -87.904842
    1615 50.026421 8.543125 1.350189 103.994433
    1619 52.461056 9.685078 47.464722 8.549167
    1625 51.432447 12.241633 48.110278 16.569722
    1628 48.353783 11.786086 41.978603 -87.904842
    1633 48.353783 11.786086 47.464722 8.549167
    1634 -1.319167 36.927500 47.464722 8.549167
    1635 49.498700 11.066897 47.464722 8.549167
    1637 48.689878 9.221964 47.464722 8.549167
    1643 50.077731 19.784836 48.110278 16.569722
    1645 52.165750 20.967122 47.464722 8.549167
    1646 53.353744 -2.274950 48.110278 16.569722
    1648 4.191833 73.529128 31.143378 121.805214
    1650 36.674900 -4.499106 47.464722 8.549167
    1652 59.651944 17.918611 47.464722 8.549167
    1653 37.936358 23.944467 47.464722 8.549167
    1657 52.453856 -1.748028 47.464722 8.549167
    1658 13.681108 100.747283 47.464722 8.549167
    1660 42.364347 -71.005181 47.464722 8.549167
    1661 50.901389 4.484444 47.464722 8.549167
    1662 47.590000 7.529167 48.110278 16.569722
    1663 47.436933 19.255592 47.464722 8.549167
    1664 30.121944 31.405556 47.464722 8.549167
    1667 55.617917 12.655972 47.464722 8.549167
    1669 42.561353 18.268244 47.464722 8.549167
    1671 55.408611 37.906111 47.464722 8.549167
    1675 40.692500 -74.168667 47.464722 8.549167
    1681 -23.432075 -46.469511 47.464722 8.549167
    1683 46.238064 6.108950 48.110278 16.569722
    1687 22.989153 -82.409086 47.464722 8.549167
    1689 22.308919 113.914603 47.464722 8.549167
    1691 38.944533 -77.455811 47.464722 8.549167
    1692 40.976922 28.814606 47.464722 8.549167
    1694 -26.139166 28.246000 47.464722 8.549167
    1695 50.345000 30.894722 47.464722 8.549167
    1696 36.080056 -115.152250 47.464722 8.549167
    1697 33.942536 -118.408075 47.464722 8.549167
    1700 59.800292 30.262503 47.464722 8.549167
    1704 46.004275 8.910578 47.464722 8.549167
    1705 49.626575 6.211517 47.464722 8.549167
    1706 45.726387 5.090833 47.464722 8.549167
    1708 53.353744 -2.274950 47.464722 8.549167
    1709 25.793250 -80.290556 47.464722 8.549167
    1712 45.630606 8.728111 47.464722 8.549167
    1714 43.658411 7.215872 47.464722 8.549167
    1715 35.764722 140.386389 47.464722 8.549167
    1718 41.978603 -87.904842 47.464722 8.549167
    1719 60.193917 11.100361 47.464722 8.549167
    1720 44.572161 26.102178 47.464722 8.549167
    1721 40.080111 116.584556 47.464722 8.549167
    1723 50.100833 14.260000 47.464722 8.549167
    1725 18.567367 -68.363431 47.464722 8.549167
    1726 31.143378 121.805214 47.464722 8.549167
    1727 31.606886 -8.036300 47.464722 8.549167
    1729 37.618972 -122.374889 47.464722 8.549167
    1730 1.350189 103.994433 47.464722 8.549167
    1732 43.538944 16.297964 47.464722 8.549167
    1735 32.011389 34.886667 47.464722 8.549167
    1736 27.975472 -82.533250 47.464722 8.549167
    1738 45.505278 12.351944 47.464722 8.549167
    1740 39.489314 -0.481625 47.464722 8.549167
    1745 45.742931 16.068778 47.464722 8.549167
    1766 24.796400 118.590000 25.077731 121.232822
    1794 12.949986 77.668206 1.350189 103.994433
    1798 11.030031 77.043383 1.350189 103.994433
    1799 29.719217 106.641678 1.350189 103.994433
    1800 18.766847 98.962644 1.350189 103.994433
    1801 10.155556 76.391389 1.350189 103.994433
    1802 28.189158 113.219633 1.350189 103.994433
    1804 16.043917 108.199370 1.350189 103.994433
    1805 -8.546553 125.524719 1.350189 103.994433
    1807 7.125522 125.645778 1.350189 103.994433
    1808 21.221192 105.807178 1.350189 103.994433
    1810 17.453117 78.467586 1.350189 103.994433
    1813 24.992364 102.743536 1.350189 103.994433
    1814 27.696583 85.359100 1.350189 103.994433
    1828 -20.430235 57.683600 40.080111 116.584556
    1829 -20.430235 57.683600 31.143378 121.805214
    1834 30.121944 31.405556 48.110278 16.569722
    1835 30.121944 31.405556 43.677223 -79.630556
    1838 25.088200 104.958700 31.143378 121.805214
    1852 43.541200 125.120100 34.447119 108.751592
    1864 31.941667 119.711667 34.447119 108.751592
    1865 40.060300 113.482000 31.143378 121.805214
    1866 31.300000 107.500000 31.143378 121.805214
    1872 -8.748169 115.167172 31.143378 121.805214
    1884 34.633000 98.867000 34.447119 108.751592
    1886 21.221192 105.807178 31.143378 121.805214
    1887 36.524000 114.430000 31.143378 121.805214
    1895 33.777200 119.147800 40.080111 116.584556
    1900 42.841400 93.669200 31.143378 121.805214
    1902 21.318681 -157.922428 31.143378 121.805214
    1906 29.934200 122.362000 31.143378 121.805214
    1914 39.856900 98.341400 34.447119 108.751592
    1915 26.899700 114.737500 34.447119 108.751592
    1916 29.515000 108.830000 40.080111 116.584556
    1917 35.417000 116.533000 40.080111 116.584556
    1921 32.857000 103.683000 34.447119 108.751592
    1922 39.542922 76.019956 34.447119 108.751592
    1948 34.410000 112.280000 40.080111 116.584556
    1949 34.550000 119.250000 40.080111 116.584556
    1950 35.046100 118.412000 40.080111 116.584556
    1951 35.046100 118.412000 31.143378 121.805214
    1952 24.207500 109.391000 31.143378 121.805214
    1953 28.852200 105.393000 40.080111 116.584556
    1954 28.852200 105.393000 31.143378 121.805214
    1960 34.991389 126.382778 31.143378 121.805214
    1962 30.754000 106.062000 31.143378 121.805214
    1965 29.826683 121.461906 34.447119 108.751592
    1969 31.742042 118.862025 31.143378 121.805214
    1972 22.608267 108.172442 1.350189 103.994433
    2010 33.585942 130.450686 1.350189 103.994433
    2018 34.434722 135.244167 1.350189 103.994433
    2023 34.858414 136.805408 1.350189 103.994433
    2029 35.764722 140.386389 48.110278 16.569722
    2036 39.457583 -74.577167 41.978603 -87.904842
    2047 33.679750 -78.928333 41.978603 -87.904842
    2048 37.721278 -122.220722 41.978603 -87.904842
    2050 31.428100 104.741000 34.447119 108.751592
    2074 44.535444 11.288667 48.110278 16.569722
    2075 50.901389 4.484444 48.110278 16.569722
    2077 47.436933 19.255592 48.110278 16.569722
    2082 46.785167 23.686167 48.110278 16.569722
    2085 42.561353 18.268244 48.110278 16.569722
    2087 36.713056 28.792500 48.110278 16.569722
    2089 48.357222 35.100556 48.110278 16.569722
    2092 36.237611 43.963158 48.110278 16.569722
    2093 40.147275 44.395881 48.110278 16.569722
    2098 46.991067 15.439628 48.110278 16.569722
    2105 49.924786 36.289986 48.110278 16.569722
    2106 38.944533 -77.455811 48.110278 16.569722
    2107 47.178492 27.620631 48.110278 16.569722
    2109 47.260219 11.343964 48.110278 16.569722
    2110 40.976922 28.814606 48.110278 16.569722
    2111 40.639751 -73.778925 48.110278 16.569722
    2113 50.345000 30.894722 48.110278 16.569722
    2114 46.927744 28.930978 48.110278 16.569722
    2115 46.642514 14.337739 48.110278 16.569722
    2117 45.034689 39.170539 48.110278 16.569722
    2118 48.663055 21.241112 48.110278 16.569722
    2120 59.800292 30.262503 48.110278 16.569722
    2123 38.781311 -9.135919 48.110278 16.569722
    2125 48.233219 14.187511 48.110278 16.569722
    2128 49.812500 23.956111 48.110278 16.569722
    2134 40.886033 14.290781 48.110278 16.569722
    2137 46.426767 30.676464 48.110278 16.569722
    2139 41.978603 -87.904842 48.110278 16.569722
    2141 44.572161 26.102178 48.110278 16.569722
    2144 38.175958 13.091019 48.110278 16.569722
    2145 50.100833 14.260000 48.110278 16.569722
    2146 42.572778 21.035833 48.110278 16.569722
    2149 47.258208 39.818089 48.110278 16.569722
    2150 45.785597 24.091342 48.110278 16.569722
    2151 43.824583 18.331467 48.110278 16.569722
    2153 41.961622 21.621381 48.110278 16.569722
    2155 43.538944 16.297964 48.110278 16.569722
    2157 38.905394 16.242269 48.110278 16.569722
    2161 42.359392 19.251894 48.110278 16.569722
    2162 41.414742 19.720561 48.110278 16.569722
    2166 43.232072 27.825106 48.110278 16.569722
    2167 45.505278 12.351944 48.110278 16.569722
    2187 -26.139166 28.246000 1.350189 103.994433
    2191 40.128082 32.995083 48.110278 16.569722
    2192 40.898553 29.309219 48.110278 16.569722
    2193 40.898553 29.309219 47.464722 8.549167
    2194 47.485033 9.560775 48.110278 16.569722
    2197 33.616653 73.099233 51.477500 -0.461389
    2199 33.616653 73.099233 43.677223 -79.630556
    2200 24.906547 67.160797 51.477500 -0.461389
    2201 24.906547 67.160797 43.677223 -79.630556
    2202 31.521564 74.403594 51.477500 -0.461389
    2203 31.521564 74.403594 43.677223 -79.630556
    2206 11.679431 122.376294 25.077731 121.232822
    2217 -9.443383 147.220050 1.350189 103.994433
    2232 25.261125 51.565056 51.477500 -0.461389
    2234 25.261125 51.565056 40.080111 116.584556
    2235 25.261125 51.565056 31.143378 121.805214
    2236 25.261125 51.565056 1.350189 103.994433
    2237 25.261125 51.565056 48.110278 16.569722
    2238 25.261125 51.565056 47.464722 8.549167
    2251 31.722556 35.993214 47.464722 8.549167
    2262 38.781311 -9.135919 43.677223 -79.630556
    2263 41.248055 -8.681389 43.677223 -79.630556
    2264 37.741184 -25.697870 43.677223 -79.630556
    2266 52.268028 104.388975 40.080111 116.584556
    2283 27.701900 118.001000 34.447119 108.751592
    2284 49.207947 -2.195508 47.464722 8.549167
    2286 59.651944 17.918611 41.978603 -87.904842
    2291 55.617917 12.655972 41.978603 -87.904842
    2293 55.617917 12.655972 31.143378 121.805214
    2294 55.617917 12.655972 1.350189 103.994433
    2300 50.901389 4.484444 41.978603 -87.904842
    2306 23.077242 72.634650 1.350189 103.994433
    2308 41.297078 2.078464 1.350189 103.994433
    2334 55.408611 37.906111 1.350189 103.994433
    2339 41.804475 12.250797 1.350189 103.994433
    2363 4.191833 73.529128 1.350189 103.994433
    2365 48.353783 11.786086 1.350189 103.994433
    2366 45.630606 8.728111 1.350189 103.994433
    2378 24.957640 46.698776 1.350189 103.994433
    2382 53.047500 8.786667 48.110278 16.569722
    2385 55.972642 37.414589 48.110278 16.569722
    2386 55.972642 37.414589 43.677223 -79.630556
    2387 55.972642 37.414589 47.464722 8.549167
    2389 21.679564 39.156536 1.350189 103.994433
    2390 21.679564 39.156536 43.677223 -79.630556
    2392 46.914100 7.497153 48.110278 16.569722
    2393 37.986814 58.360967 51.477500 -0.461389
    2408 40.976922 28.814606 41.978603 -87.904842
    2436 6.933206 100.392975 1.350189 103.994433
    2445 26.883333 100.233330 1.350189 103.994433
    2447 22.149556 113.591558 1.350189 103.994433
    2450 29.826683 121.461906 1.350189 103.994433
    2458 37.936358 23.944467 43.677223 -79.630556
    2465 55.871944 -4.433056 43.677223 -79.630556
    2467 51.148056 -0.190278 43.677223 -79.630556
    2469 53.353744 -2.274950 43.677223 -79.630556
    2474 45.505278 12.351944 43.677223 -79.630556
    2477 33.875031 10.775461 47.464722 8.549167
    2478 36.075833 10.438611 47.464722 8.549167
    2479 36.851033 10.227217 48.110278 16.569722
    2480 36.851033 10.227217 47.464722 8.549167
    2485 31.742042 118.862025 1.350189 103.994433
    2487 -28.164444 153.504722 1.350189 103.994433
    2490 51.148056 -0.190278 48.110278 16.569722
    2491 51.148056 -0.190278 47.464722 8.549167
    2492 51.874722 -0.368333 47.464722 8.549167
    2493 40.652083 -75.440806 41.978603 -87.904842
    2496 42.748267 -73.801692 41.978603 -87.904842
    2501 44.257526 -88.507576 41.978603 -87.904842
    2503 35.436194 -82.541806 41.978603 -87.904842
    2504 41.338478 -75.723403 41.978603 -87.904842
    2507 33.562942 -86.753550 41.978603 -87.904842
    2509 43.564361 -116.222861 41.978603 -87.904842
    2514 44.471861 -73.153278 41.978603 -87.904842
    2517 45.777643 -111.160151 41.978603 -87.904842
    2518 33.938833 -81.119528 41.978603 -87.904842
    2519 40.916083 -81.442194 41.978603 -87.904842
    2521 32.898647 -80.040528 41.978603 -87.904842
    2528 47.168400 -88.489100 41.978603 -87.904842
    2529 38.805805 -104.700778 41.978603 -87.904842
    2539 46.842091 -92.193649 41.978603 -87.904842
    2546 44.865800 -91.484300 41.978603 -87.904842
    2547 42.159889 -76.891611 41.978603 -87.904842
    2557 38.950944 -95.663611 41.978603 -87.904842
    2563 -23.432075 -46.469511 41.978603 -87.904842
    2564 36.097750 -79.937306 41.978603 -87.904842
    2565 34.895556 -82.218889 41.978603 -87.904842
    2568 21.318681 -157.922428 41.978603 -87.904842
    2573 38.944533 -77.455811 41.978603 -87.904842
    2584 32.311167 -90.075889 41.978603 -87.904842
    2589 42.778700 -84.587357 41.978603 -87.904842
    2603 40.850971 -96.759250 41.978603 -87.904842
    2604 43.532913 -84.079647 41.978603 -87.904842
    2610 42.932556 -71.435667 41.978603 -87.904842
    2614 43.169500 -86.238200 41.978603 -87.904842
    2616 30.691231 -88.242814 41.978603 -87.904842
    2622 25.778489 -100.106878 41.978603 -87.904842
    2625 25.038958 -77.466231 41.978603 -87.904842
    2629 20.898650 -156.430458 41.978603 -87.904842
    2644 7.180756 79.884117 51.477500 -0.461389
    2645 7.180756 79.884117 40.080111 116.584556
    2646 7.180756 79.884117 31.143378 121.805214
    2648 6.284467 81.124128 40.080111 116.584556
    2649 6.284467 81.124128 31.143378 121.805214
    2650 23.593278 58.284444 47.464722 8.549167
    2659 55.591531 37.261486 43.677223 -79.630556
    2783 16.043917 108.199370 31.143378 121.805214
    2817 53.047500 8.786667 47.464722 8.549167
    2818 52.134642 7.684831 47.464722 8.549167
    2819 35.416111 51.152222 31.143378 121.805214
    2843 33.679750 -78.928333 43.677223 -79.630556
    2851 18.439417 -66.001833 43.677223 -79.630556
    2853 18.040953 -63.108900 43.677223 -79.630556
    2860 49.956112 -119.377778 43.677223 -79.630556
    2877 38.292392 27.156953 48.110278 16.569722
    2878 38.292392 27.156953 47.464722 8.549167
    2885 42.359392 19.251894 47.464722 8.549167
    # Get a nice image of the globe from NASA
    earth <- "http://eoimages.gsfc.nasa.gov/images/imagerecords/73000/73909/world.topo.bathy.200412.3x5400x2700.jpg"
    
    globejs(
      img = earth,
      lat = frequent_flights$dest_lat,
      long = frequent_flights$dest_long,
      arcs = frequent_flights,
      # value = frequent_destinations$n,
      color = "red",
      # bodycolor = "#aaaaff",
      arcsHeight = 0.3,
      arcsLwd = 2,
      arcsColor = "#ffff00",
      arcsOpacity = 0.35,
      atmosphere = FALSE,
      # color="#00aaff",
      pointsize = 2,
      rotationlat = 0.6,
      rotationlong = 0.2,
      # lightcolor = "#aaeeff",
      # emissive = "#0000ee",
      # bodycolor = "#ffffff",
      bg = "grey"
    )

    Using scatterplot3js and friends

    3D scatter plots with points and lines can be achieved using scatterplot3js, points3D, and lines3D.

    library(palmerpenguins)
    penguins <- penguins %>% drop_na()
    scatterplot3js(
      x = penguins$bill_length_mm,
      y = penguins$flipper_length_mm,
      z = penguins$body_mass_g
    )

    library(palmerpenguins)
    penguins <- penguins %>% drop_na()
    scatterplot3js(
      x = penguins$bill_length_mm,
      y = penguins$flipper_length_mm,
      z = penguins$body_mass_g,
      cex.symbols = 0.2
    ) # Smaller Points

    library(palmerpenguins)
    penguins <- penguins %>% drop_na()
    
    scatterplot3js(
      x = penguins$bill_length_mm,
      y = penguins$flipper_length_mm,
      z = penguins$body_mass_g,
      cex.symbols = 0.2
    ) # Smaller Points

    References

    1. Bring the best of JavaScript data visualization to R, https://www.htmlwidgets.org/

    2. Using htmlwidgets in Rmarkdown, https://communicate-data-with-r.netlify.app/docs/communicate/htmlwidgets-in-documents/

    3. Karambelkar et al, htmlwidgets and knitr , https://cran.r-project.org/web/packages/widgetframe/vignettes/widgetframe_and_knitr.html

    4. The patchwork package to combine plots. https://patchwork.data-imaginist.com/

    5. The threejs package: three.js widgets for R https://bwlewis.github.io/rthreejs/

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